scholarly journals 3-Level Service Composition and Cashew: A Model for Orchestration and Choreography in Semantic Web Services

2006 ◽  
pp. 58-67 ◽  
Author(s):  
Barry Norton ◽  
Carlos Pedrinaci
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Service Composition ◽  
Semantic Web Services

Service Composition and Execution Plan Generation of Composite Semantic WEB Services Using Abductive Event Calculus

2015 ◽  
Vol 32 (4) ◽  
pp. 711-737 ◽  
Author(s):  
D. Paulraj ◽  
S. Swamynathan ◽  
Daniel Chandran ◽  
K. Balasubadra ◽  
M. Vigilson Prem
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Service Composition ◽  
Semantic Web Services ◽  
Event Calculus ◽  
Execution Plan ◽  
Plan Generation

Semantic Web Services for Healthcare

2011 ◽  
pp. 765-773
Author(s):  
Christina Catley ◽  
Monique Frize ◽  
Dorina Petriu
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Service Composition ◽  
Value Added ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Semantic Web Services ◽  
Healthcare Data ◽  
Critical Issues ◽  
Clinical Environments

This chapter explores the ongoing efforts to integrate Web services and the Semantic Web for the purposes of sharing knowledge, enabling access to services, and application integration in distributed clinical environments. Combining the Semantic Web and Web services in relation to the healthcare domain, results in Semantic Web services for healthcare, which will enable intelligent interpretation of healthcare data by services such as clinical decision support systems. Critical issues in ontology standardization and security are discussed. The multi-disciplinary problem of service composition is presented with emphasis on the role healthcare experts play in identifying value-added medical services.

Semantic Web Services for Healthcare

2011 ◽  
pp. 262-270
Author(s):  
Christina Catley ◽  
Monique Frize ◽  
Dorina Petriu
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Service Composition ◽  
Value Added ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Semantic Web Services ◽  
Healthcare Data ◽  
Critical Issues ◽  
Clinical Environments

This chapter explores the ongoing efforts to integrate Web services and the Semantic Web for the purposes of sharing knowledge, enabling access to services, and application integration in distributed clinical environments. Combining the Semantic Web and Web services in relation to the healthcare domain, results in Semantic Web services for healthcare, which will enable intelligent interpretation of healthcare data by services such as clinical decision support systems. Critical issues in ontology standardization and security are discussed. The multi-disciplinary problem of service composition is presented with emphasis on the role healthcare experts play in identifying value-added medical services.

PROCESS MODEL ONTOLOGY-BASED MATCHMAKING OF SEMANTIC WEB SERVICES

2011 ◽  
Vol 20 (04) ◽  
pp. 357-370 ◽  
Author(s):  
D. PAULRAJ ◽  
S. SWAMYNATHAN ◽  
M. MADHAIYAN
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Web Service ◽  
Process Model ◽  
Service Discovery ◽  
Service Oriented Architecture ◽  
Semantic Web Services ◽  
Functional Part ◽  
Service Oriented ◽  
Concise Description

One of the key challenges of the Service Oriented Architecture is the discovery of relevant services for a given task. In Semantic Web Services, service discovery is generally achieved by using the service profile ontology of OWL-S. Profile of a service is a derived, concise description and not a functional part of the semantic web service. There is no schema present in the service profile to describe the input, output (IO), and the IOs in the service profile are not always annotated with ontology concepts, whereas the process model has such a schema to describe the IOs which are always annotated with ontology concepts. In this paper, we propose a complementary sophisticated matchmaking approach which uses the concrete process model ontology of OWL-S instead of the concise service profile ontology. Empirical analysis shows that high precision and recall can be achieved by using the process model-based service discovery.

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